HAZARD
Climate variables and hazards considered in the study. As first step the relevant climate variables are selected and serve as a base to derive climate indices necessary for the hazard analysis. For each climate-related hazard one or more relevant indices, such as probability of occurrence, exceedances over threshold values, are identified. The indices are calculated for a defined climatic period and climate variables can be combined with other parameters to evaluate characteristics of more complex natural hazards, such as landslides or floods. Given a defined hazard scale, the hazard conditions in the project area can be quantified.
BARCELONA RESEARCH SITES
In the case study of Barcelona, a comprehensive multi-risk assessment was performed concerning several sectors and risk targets exposed to urban flooding. Risk assessment in Barcelona considered direct and indirect damage, as such as, tangible and intangible damages. Direct damages were also represented through qualitative (for the intangible impacts) and quantitative (for tangible impacts) maps achieved by sectorial and integrated detailed and calibrated models.
In this web-portal, hazard, vulnerability and risk maps elaborated for current (Baseline) and future (Business as Usual or BAU and Adaptation) scenarios are presented. These flood maps related to pluvial and coastal flooding focused on the following potential impacts:
- Risk for people (Stability of pedestrians and vehicles)
- Economic damage related to properties
- Economic damage related to vehicles
- Surface traffic disruption
- Waste containers stability
- Flooding of coastal critical infrastructures and services
1. Risk for people (Stability of pedestrians and vehicles)
Description of variables and indices.
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Flow depth and velocity are the hydraulic variables that mainly affect the stability of pedestrian and vehicles in case of floods. In case of pluvial urban floods runoff is characterized by high flow velocity and reduced flow depths.
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Data sources
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This study is based on the data related to two experimental campaigns undertaken at the Universitat Politècnica de Catalunya (Russo et al., 2013; Martínez-Gomariz et al., 2016; 2017). According to these researches’ outcomes hazards levels have been proposed here.
For further information see:
Russo, B., Gómez, M., Macchione, F., 2013. Pedestrian hazard criteria for flooded urban areas. Nat. Hazards 69, 251–265. https://doi.org/10.1007/s11069-013-0702-2
Martínez-Gomariz, E.; Gómez, M.; Russo, B. Experimental study of the stability of pedestrians exposed to urban pluvial flooding. Nat. Hazards 2016, 82, 1259–1278.
Martínez-Gomariz, E.; Gómez, M.; Russo, B.; Djordjević, S. A new experiments-based methodology to define the stability threshold for any vehicle exposed to flooding. Urban Water J. 2017, 14, 930–939.
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Scale of work or resolution
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City Scale
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Methodology
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The hydrodynamic model output (i.e. velocities and water depths per grid cell) have been transformed into hazard level according to the thresholds proposed here.

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Uncertainty
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The uncertainty falls mainly on the person’ and vehicle’s profile which may be different from the ones considered in the study.
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Maps description
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The hazard map represents the levels of likelihood for either a pedestrian or a vehicle to loss their stability. High-risks areas in these maps indicate those areas where the hydrodynamic variables are able to cause an instability for a person and vehicle respectively.
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Projection and reference system
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SGR ETRS 1989 UTM (31N)
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Type
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Public
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License
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Free
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Data set (Raster/shp )
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Geo-referenced information obtained
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Main participants
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Eduardo Martínez-Gomariz, Cetaqua, Water Technology Centre
Edwar Forero-Ortiz, Cetaqua, Water Technology Centre
Beniamino Russo, Aquatec, SUEZ Water Advanced Solutions
Luca Locatelli, Aquatec, SUEZ Water Advanced Solutions
Dani Yubero, Aquatec, SUEZ Water Advanced Solutions
Maria Guerrero-Hidalga, Cetaqua, Water Technology Centre
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2. Economic damage related to properties
Description of variables and indices.
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Only water depth has been considered as a main driver for direct damage to property.
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Data sources
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Flood maps provided through 1D/2D hydrodynamic model
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Projection and reference system
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SGR ETRS 1989 UTM (31N)
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Scale of work or resolution
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City scale
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Methodology
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1D/2D hydrodynamic model provide flood depth on surface for each cell of the 2D domain. These flood depths are used to estimate flood depth inside the building according to building type and configuration and through a specific methodology validated in the flood damage model.
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Uncertainty
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Flood depths accuracy depends on the size of the surface cells and the goodness of the 1D/2D hydrodynamic model.
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Maps description
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Being this an intermediate process, maps have not been developed.
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Projection and reference system
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SGR ETRS 1989 UTM (31N)
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Type
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License
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Data set (Raster/shp )
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Main participants
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Eduardo Martínez-Gomariz, Cetaqua, Water Technology Centre
Edwar Forero-Ortiz, Cetaqua, Water Technology Centre
Beniamino Russo, Aquatec, SUEZ Water Advanced Solutions
Luca Locatelli, Aquatec, SUEZ Water Advanced Solutions
Maria Guerrero-Hidalga, Cetaqua, Water Technology Centre
Dani Yubero, Aquatec, SUEZ Water Advanced Solutions
Salvador Castan, Agencia Pericial (Insurance Company) (AGPERICIAL)
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3. Economic damage related to vehicles
Description of variables and indices.
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Only water depth has been considered as a main driver for direct damage to property.
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Data sources
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Flood maps provided through 1D/2D hydrodynamic model
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Projection and reference system
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SGR ETRS 1989 UTM (31N)
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Scale of work or resolution
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City scale
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Methodology
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1D/2D hydrodynamic model provide flood depth on surface for each cell of the 2D domain. These flood depths are used to estimate flood depth inside the building according to building type and configuration and through a specific methodology validated in the flood damage model.
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Uncertainty
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Flood depths accuracy depends on the size of the surface cells and the goodness of the 1D/2D hydrodynamic model.
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Maps description
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Being this an intermediate process, maps have not been developed.
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Projection and reference system
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SGR ETRS 1989 UTM (31N)
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Type
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License
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Data set (Raster/shp )
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Main participants
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Eduardo Martínez-Gomariz, Cetaqua, Water Technology Centre
Edwar Forero-Ortiz, Cetaqua, Water Technology Centre
Beniamino Russo, Aquatec, SUEZ Water Advanced Solutions
Luca Locatelli, Aquatec, SUEZ Water Advanced Solutions
Maria Guerrero-Hidalga, Cetaqua, Water Technology Centre
Dani Yubero, Aquatec, SUEZ Water Advanced Solutions
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4. Surface traffic disruption
Description of variables and indices.
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Water depth has been considered as a main variable to elaborate hazard maps.
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Data sources
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Flood maps provided through 1D/2D hydrodynamic model
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Projection and reference system
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SGR ETRS 1989 UTM (31N)
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Scale of work or resolution
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City scale
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Methodology
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1D/2D hydrodynamic model provide flood depth on surface for each cell of the 2D domain. These flood depths are used to elaborate hazard maps according to specific hazard criteria.
For the assessment of flood hazard upon the road infrastructure a GIS base spatial analysis has been carried out (Figure 1) and the rules about traffic speed reduction (Table 1) have been applied (Paytkova et al., 2019). The outputs of this model have been used by Traffic model to estimate pluvial flood impacts on traffic service.
 Figure 1: Linking flood model outputs with traffic models.
Table 2: Parameters for determining effects of flood depths on traffic speed.
Flood Depth Range (cm)
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Maximum Permitted Speed kmh-1
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0.00 – 10.00
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Roads maximum speed
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10.00 – 30.00
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20
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30.00 +
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0 (Road closed)
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References:
Pyatkova K. Chen A. S., Djordjevic S., Butler D., Vojinovic Z., Abebe Y. A., Hammond M. Flood Impacts on Road transportation Using Microscopic Traffic Modelling Technique [Conference]. - [s.l.]: SUMO User Conference, 2015.
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Uncertainty
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Flood depths accuracy depends on the size of the surface cells and the goodness of the 1D/2D hydrodynamic model.
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Maps description
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According to the exposed methodology, qualitative hazard maps have been elaborated classifying hazard by three levels: low, medium and high (Table 2).
Table 2: Flood hazard classification.
Flood depth range (m)
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Hazard classification
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Maximum Vehicle speed (km/h)
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Flow depth < 0.1
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Low
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Road speed limit
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0.1 < Flow depth < 0.3
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Medium
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20
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Flow depth > 0.3 m
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High
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0 (Road closed)
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Projection and reference system
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SGR ETRS 1989 UTM (31N)
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Type
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Public
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License
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Free
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Data set (Raster/shp )
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geo-referenced information obtained
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Main participants
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Andoni Gonzalez, Barcelona Municipality
Barry Evans, University of Exeter
Beniamino Russo, Aquatec, SUEZ Water Advanced Solutions
Dani Yubero, Aquatec, SUEZ Water Advanced Solutions
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5. Waste containers stability
Description of variables and indices.
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Containers’ stability may be compromised when the hydrodynamic variables, water depth and velocity, exceed a certain threshold.
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Data sources
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Flood maps provided through 1D/2D hydrodynamic model
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Projection and reference system
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SGR ETRS 1989 UTM (31N)
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Scale of work or resolution
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City scale
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Methodology
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1D/2D hydrodynamic model provide flood depth and velocity on surface for each cell of the 2D domain. These variables corresponding to the location of waste containers have been combined and compared to sliding and toppling stability thresholds.
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Uncertainty
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Flood depths accuracy depends on the size of the surface cells and the goodness of the 1D/2D hydrodynamic model.
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Maps description
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Being this an intermediate process, maps have not been developed.
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Projection and reference system
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SGR ETRS 1989 UTM (31N)
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Type
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License
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Data set (Raster/shp )
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Main participants
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Eduardo Martínez-Gomariz, Cetaqua, Water Technology Centre
Beniamino Russo, Aquatec, SUEZ Water Advanced Solutions
Dani Yubero, Aquatec, SUEZ Water Advanced Solutions
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6. Flooding of coastal critical infrastructures and services
Description of variables and indices.
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Flood extension has been used as the unique indicator in this analysis.
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Data sources
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Flood maps provided GIS analysis
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Projection and reference system
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SGR ETRS 1989 UTM (31N)
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Scale of work or resolution
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City scale
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Methodology
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Sea level rises produced by RCPs 4.5 and 8.5 and coastal bathymetry have been crossed to assess the area potentially covered for the horizon of 2100.
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Uncertainty
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Flooded areas depend on the climate predictions and bathymetry and accuracy.
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Maps description
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Being this an intermediate process, maps have not been developed.
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Projection and reference system
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SGR ETRS 1989 UTM (31N)
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Type
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License
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Data set (Raster/shp )
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Main participants
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Beniamino Russo, Aquatec, SUEZ Water Advanced Solutions
Luca Locatelli, SUEZ Water Advanced Solutions
Dani Yubero, Aquatec, SUEZ Water Advanced Solutions
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